As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.
Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines – from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards
Requirements:
5+ years in ML roles with demonstrated production impact
Advanced degree (MS/PhD) in a quantitative field, or equivalent industry depth
Deep expertise in mathematical optimization – convex, constrained, and gradient-based methods
Hands-on experience with Bayesian or hyperparameter optimization
Strong causal inference skills – propensity scoring, uplift modeling, or experimental design
Applied ML experience in optimization domains: pricing, bidding, or resource allocation
Advanced time series modeling for dynamic, decision-making systems
Proven experience deploying and monitoring real-time ML models in production
Familiarity with experiment tracking, model versioning, and performance monitoring
5+ years in ML roles with demonstrated production impact
Advanced degree (MS/PhD) in a quantitative field, or equivalent industry depth
Deep expertise in mathematical optimization – convex, constrained, and gradient-based methods
Hands-on experience with Bayesian or hyperparameter optimization
Strong causal inference skills – propensity scoring, uplift modeling, or experimental design
Applied ML experience in optimization domains: pricing, bidding, or resource allocation
Advanced time series modeling for dynamic, decision-making systems
Proven experience deploying and monitoring real-time ML models in production
Familiarity with experiment tracking, model versioning, and performance monitoring
This position is open to all candidates.
